Two novel online nomograms for predicting the survival of individual patients undergoing partial hepatectomy for huge hepatocellular carcinoma

Chen, Zixiang; Cai, Ming; Wang, Xu; Zhou, Yi; Chen, Jiangming; Xie, Qing; Zhao, Yupei; Xie, Kun; Fang, Qiang; Tian, Pu; Jiang, Donghua; Bai, Tao; Ma, Jun; Geng, Xiaoping; Liu, Fubao

doi:10.1016/j.hpb.2020.12.002

Cited by 2 publications

(4 citation statements)

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“…It may be helpful to assist in making a precisely prognostic evaluation, therapeutic selection, and individual follow‐up strategy. Although some predictive models evaluating the prognosis of MHCC exist, they were mainly developed based on cases from a single race/region, and did not discuss whether other treatment strategies could impact the prognosis of MHCC or not 19,20 . The SEER database, an authoritative source, provides many cross‐race cases with detailed information for studies.…”

Section: Discussionmentioning

confidence: 99%

“…Although some predictive models evaluating the prognosis of MHCC exist, they were mainly developed based on cases from a single race/region, and did not discuss whether other treatment strategies could impact the prognosis of MHCC or not. 19 , 20 The SEER database, an authoritative source, provides many cross‐race cases with detailed information for studies. Based on data from the database, we constructed and validated the prognostic models for MHCC with more persuasiveness.…”

Section: Discussionmentioning

confidence: 99%

“…Numerous studies showed that they all were associated with the prognosis of HCC. 34 , 35 , 36 , 37 Chen et al 20 figured out that both cirrhosis and AFP were significantly independent factors of OS for HCC. Meanwhile, compared with the non‐MHCC set, the MHCC set had a higher level of preoperative AFP.…”

Section: Discussionmentioning

confidence: 99%

“…Limited by lagging in data updates of the SEER database, we excluded the patients from before 2010 and from 2015 onwards to reduce calculative bias caused by vast missing data of some variables. (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) cm or >20 cm), grade (grade I/II or III/IV), stage according to the 7th AJCC-TNM staging system, combined summary stage (localized, regional or distant)], therapeutic strategies (with or without surgery, with or without radiotherapy, and with or without chemotherapy), survival condition (survival months and vital status). Notably, as for histological grade of differentiation, grade I/II refers to a well or a moderately differentiated tumor while grade III/IV means a poorly differentiated or an undifferentiated tumor.…”

Section: Patient Selectionmentioning

confidence: 99%

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Development and validation of web‐based prognostic nomograms for massive hepatocellular carcinoma (≥10 cm): A retrospective study based on the SEER database

et al. 2023

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Background and Aims Massive hepatocellular carcinoma (MHCC, a maximum tumor size of at least 10 cm) tends to have a poor prognosis. Therefore, this study aims to construct and validate prognostic nomograms for MHCC. Methods Clinic data of 1292 MHCC patients between 2010 and 2015 were got from the surveillance, epidemiology, and end results (SEER) cancer registration database. The whole set was separated into the training and validation sets at a ratio of 2:1 randomly. Variables, significantly associated with cancer‐specific (CSS) and overall survival (OS) of MHCC were figured out by multivariate Cox regression analysis and were taken to develop nomograms. The concordance index (C‐index), calibration curve, and decision curve analysis (DCA) were taken to validate the predictive abilities and accuracy of the nomograms. Results Race, alpha‐fetoprotein (AFP), grade, combined summary stage, and surgery were identified as independent factors of CSS, and fibrosis score, AFP, grade, combined summary stage, and surgery significantly correlated with OS in the training cohort. They then were taken to construct prognostic nomograms. The constructed model for predicting CSS exhibited satisfactory performance with a C‐index of 0.727 (95% CI: 0.746–0.708) in the training group and 0. 672 (95% CI: 0.703–0.641) in the validation group. Besides, the model for predicting OS of MHCC also showed strong performance both in the training group (C‐index: 0.722, 95% CI: 0.741–0.704) and the validation (C‐index: 0.667, 95% CI: 0.696–0.638) group. All calibration curves and decision curves performed satisfactory predictive accuracy and clinic application values of the nomograms. Conclusion The web‐based nomograms for CSS and OS of MHCC were developed and validated in this study, which prospectively could be tested and may serve as additional tools to assess patient's individualized prognosis and make precise therapeutic selection to improve the poor outcome of MHCC.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%